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| 1 | Distribution and sources of solvent extractable organic compounds in PM_(2.5) during 2007 Chinese Spring Festival in Beijing显示文摘The solvent extractable organic compounds (SEOC), including n-alkanes, polycylic aromatic hydrocarbons, fatty acids, anddicarboxylic acids in PM2.5 during the 2007 Chinese Spring Festival in Beijing, were measured via gas chromatography-massspectrometry for determining the characteristics and sources of these organic pollutants. The concentrations of total n-alkanes, PAHs,and organic acids before Chinese Spring Festival Eve (1025.5, 95.9, and 543.3 ng/m3, respectively) were higher than those after (536.6,58.9, and 331.8 ng/m3, respectively). n-Aalkanes and PAHs had much higher concentration in nighttime than those in daytime becauseof high relative humidity and low wind speed during the night. Combustion of coal and exhaust emission were major sources of n-alkanes. It could be concluded by the characteristic ratios that the primary source of PAHs in fine particles was the combustion of coal,but the combustion of gasoline was in the next place. The ratios of C18:0/C16 indicated the contribution of vehicular emissions to thefatty acids. Dicarboxylic and aromatic acids were abundant in daytime than in nighttime because these acids were secondary organicacid and the photochemical degradation of aromatic hydrocarbons was the main source. | LI Xingru GUO Xueqing LIU Xinran LIU Chenshu ZHANG Shanshan WANG Yuesi | 2009 | Journal of Environmental Sciences2009，21，2： | 17 |
| 2 | Sensorless Sensing with WiFi显示文摘Can WiFi signals be used for sensing purpose? The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacy-preserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world's largest wireless sensor networks. Yet the concept of wireless and sensorless sensing is not the simple combination of WiFi and radar. It seeks breakthroughs from dedicated radar systems, and aims to balance between low cost and high accuracy, to meet the rising demand for pervasive environment perception in everyday life. Despite increasing research interest, wireless sensing is still in its infancy. Through introductions on basic principles and working prototypes, we review the feasibilities and limitations of wireless, sensorless, and contactless sensing via WiFi. We envision this article as a brief primer on wireless sensing for interested readers to explore this open and largely unexplored field and create next-generation wireless and mobile computing applications. | Zimu Zhou Chenshu Wu Zheng Yang Yunhao Liu | 2015 | Tsinghua Science and Technology2015，20，1： | 9 |
| 3 | WiSH:WiFi-Based Real-Time Human Detection显示文摘Sensorless sensing using wireless signals has been rapidly conceptualized and developed recently. Among numerous applications of WiFi-based sensing, human presence detection acts as a primary and fundamental function to boost applications in practice. Many complicated approaches have been proposed to achieve high detection accuracy, but they frequently omit various practical constraints such as real-time capability, computation efficiency, sampling rates, deployment efforts, etc. A practical detection system that works in realworld applicati ons is lacki ng. In this paper, we design and implement WiSH, a real-time system for con tactless human detection that is applicable for whole-day usage. WiSH employs lightweight yet effective methods and thus enables detection under practical conditions even on resource-limited devices with low signal sampling rates. We deploy WiSH on commodity desktops and customized tiny no des in different everyday scenarios. The experimental results dem on strate the superior performance of WiSH, which has a detection accuracy of >98% using a sampling rate of 20 Hz with an average detection delay of merely 1.5 s. Thus, we believe WiSH is a promising system for real-world deployment. | Tianmeng Hang Yue Zheng Kun Qian Chenshu Wu Zheng Yang Xiancun Zhou Yunhao Liu Guilin Chen | 2019 | Tsinghua Science and Technology2019，24，5： | 2 |
| 4 | Locating in FingerprintSpace : Wireless Indoor Localization with Little Human Intervention显示文摘 | Zheng Yang Chenshu Wu Yunhao Liu | 2012 | In Proceedings of ACM MobiCom2012，，8： | 1 |
| 5 | Detectingoutlier measurements based on graph rigidity for wirelesssensor network localization 显示文摘 | Yang Zhen Wu Chenshu Liu Yunhao | 2013 | IEEE Trans on VehicularTechnology2013，62，1： | 1 |
| 6 | COVID-19 induces new-onset insulin resistance and lipid metabolic dysregulation via regulation of secreted metabolic factors显示文摘Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism.In this study,we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases,and found new-onset in suli n resista nee,hyperglycemia,and decreased HDL-C in these patie nts.Mecha nistically,SARS-CoV-2 infecti on in creased the expression of RE1-silencing transcription factor(REST),which modulated the expression of secreted metabolic factors including myeloperoxidase,apelin,and myostatin at the transcriptional level,resulting in the perturbation of glucose and lipid metabolism.Furthermore,several lipids,including(±)5-HETE,(±)12-HETE,propionic acid,and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation,especially in insulin resistance.Taken together,our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19,and further illustrated the underlying mechanisms,providing potential therapeutic targets for COVID-19-induced metabolic complications. | Xi He Chenshu Liu Jiangyun Peng Zilun Li Fang Li Jian Wang Ao Hu Meixiu Peng Kan Huang Dongxiao Fan Na Li Fuchun Zhang Weiping Cai Xinghua Tan Zhongwei Hu Xilong Deng Yueping Li Xiaoneng Mo Linghua Li Yaling Shi Li Yang Yuanyuan Zhu Yanrong Wu Huichao Liang Baolin Liao Wenxin Hong Ruiying He Jiaojiao Li Pengle Guo Youguang Zhuo Lingzhai Zhao Fengyu Hu Wenxue Li Wei Zhu Zefeng Zhang Zeling Guo Wei Zhang Xiqiang Hong Wei kang Cai Lei Gu Ziming Du Yang Zhang Jin Xu Tao Zuo Kai Deng Li Yan Xinwen Chen Sifan Chen Chunliang Lei | 2022 | Signal Transduction and Targeted Therapy2022，7，1： | 0 |
| 7 | Leveraging Logical Anchor into Topology Optimization forIndoor Wireless Fingerprinting显示文摘The indoor subarea localization has wide application space in dynamic hotzone identification, indoor layout optimization, store dynamic pricing and crowd flowtrend prediction. The ubiquitous mobile devices provide the opportunity for wirelessfingerprinting-based indoor localization services. However, there are two short boardwhere the existing methods have been criticized. One is that a tagging approach requiresa large number of professional surveys for wireless fingerprint construction, whichweakens the scalability of the methods. The other is that the crowdsourcing-basedmethods encounter the cold boot problem in the system initial stage. To address theseissues, the paper proposes a topology optimization approach leveraging the dynamiclogical anchor selection into a subarea localization system. First of all, a newannular-based radio map construction strategy with the feedback selection of logic anchoris designed to release the pressure of site survey. The implementation of this strategyharnesses the characteristics of the indoor building structure and inter subareaoverlapping recognition, without the topology and distribution of physical anchor (e.g.,access points or POIs). Secondly, exploiting the probabilistic support vector machinealgorithm, the target is localized in the corresponding subarea in a real-time pattern.Furthermore, the localization error is calibrated with an error recognition algorithm.Finally, massive experiments are implemented on a prototype system. The results showthat the proposed method can decrease the overhead of the system initialization andachieve higher localization accuracy compared with the existing approaches. | Lin Wang Huixiang Liu Wenyuan Liu Nan Jing Ahmad Adnan Chenshu Wu | 2019 | Computers, Materials & Continua2019，，2： | 0 |
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